DFT vs. DTFT: Understanding the Difference

In summary: You get the spectrum of the original signal by assuming that it is zero outside of the interval that you have sampled.In summary, the conversation discussed the differences between DFT and DTFT and how they relate to the spectrum of a sampled signal. The DTFT gives us the spectrum of the sampled original signal, while the DFT is derived from the DTFT and represents the frequency domain of a finite sequence assumed to be a single period of a periodic function. There was confusion about the use of ##X(\omega)## in the equations, as it is not the spectrum of the original continuous time function but rather the spectrum of the finite sequence assumed to be periodic.
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CoolDude420
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Homework Statement


I'm kind of confused between DFT and DTFT. Here is my understanding:

Okay, so let's say we have time domain, continuous, analogue signal from a sensor - ##x(t) ##
96930eb80e.png


1. We sample this signal, giving us something like the following with an impulse train
a73229dd51.png

Now this is a discrete-time sequence ##x_n ##. So we can apply the Discrete-Time Fourier Transform to obtain the spectrum of this discrete sequence ##x_n ## - let's call that ##X_s(w) ##. The DTFT is stated as follows,
534941e211.png


Thus, the DTFT gives us the spectrum of the SAMPLED original signal. Correct?

Now, to use the DTFT in a computer, we cannot have an inifnite summation, thus we change to using N because it is periodic with a period of 2pi. So my lecture notes is beginning to derive the DFT from the DTFT, so it says this now,

8ad51487b9.png

Note that this is not the full DFT, it's in the process of deriving.

Here is my confusion. How come this equation has ##X(w)##, i.e the spectrum of the very original signal. But the DTFT formula has ##X_s(w)##, the spectrum of the sampled signal?? Is there a mistake in the notes? How did we magically just get back the spectrum of the original signal when we were infact dealing with the spectrum of the sampled signal?

Homework Equations

The Attempt at a Solution

 

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  • #2
CoolDude420 said:
Thus, the DTFT gives us the spectrum of the SAMPLED original signal. Correct?
Correct.

CoolDude420 said:
Now, to use the DTFT in a computer, we cannot have an inifnite summation, thus we change to using N because it is periodic with a period of 2pi.
Actually, the fact is that you have a finite number of numbers in your sequence. There is more than one thing you can conceivably do with that (for example, you could assume that the function is zero everywhere else), but if you assume that your finite sequence is a single period of a periodic function then the DFT is the natural frequency domain representation.

CoolDude420 said:
Here is my confusion. How come this equation has ##X(w)##, i.e the spectrum of the very original signal. But the DTFT formula has ##X_s(w)##, the spectrum of the sampled signal?? Is there a mistake in the notes? How did we magically just get back the spectrum of the original signal when we were infact dealing with the spectrum of the sampled signal?
The ##X(\omega)## above is not the spectrum of the original continuous time function. You do not get the spectrum of the original signal by sampling a finite length of it and then assuming it is periodic.
 
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1. What is the difference between DFT and DTFT?

DFT (Discrete Fourier Transform) and DTFT (Discrete-Time Fourier Transform) are both mathematical tools used to represent a signal in the frequency domain. The main difference between the two is that DFT is used for discrete-time signals, while DTFT is used for continuous-time signals.

2. Which one is more commonly used in practice?

In practice, DFT is more commonly used because it can be implemented on digital computers and is more efficient for analyzing discrete-time signals. DTFT is used for theoretical analysis and to understand the frequency characteristics of continuous-time signals.

3. Can DFT and DTFT be used interchangeably?

No, DFT and DTFT cannot be used interchangeably. DFT is a discrete version of DTFT and is only applicable to discrete-time signals, while DTFT is used for continuous-time signals. Attempting to use DFT on a continuous-time signal will result in inaccurate results.

4. How do DFT and DTFT relate to each other?

DFT is a sampled version of DTFT. This means that DFT is obtained by sampling a continuous signal in the time domain and then using DTFT to analyze the sampled signal in the frequency domain.

5. What are the advantages and disadvantages of using DFT and DTFT?

The main advantage of using DFT is that it can be easily implemented on digital computers, making it more practical for analyzing discrete-time signals. On the other hand, DTFT is more suitable for theoretical analysis of continuous-time signals, but it cannot be implemented on digital computers. The disadvantage of DFT is that it can only be used on discrete-time signals, while the disadvantage of DTFT is that it is not easily implementable on digital computers.

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